Antonio Jose Rodríguez-Sánchez
Orcid: 0000-0002-3264-5060
According to our database1,
Antonio Jose Rodríguez-Sánchez
authored at least 57 papers
between 2006 and 2023.
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Bibliography
2023
Robotics Auton. Syst., 2023
Scalable and Efficient Continual Learning from Demonstration via Hypernetwork-generated Stable Dynamics Model.
CoRR, 2023
2022
Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization.
Trans. Mach. Learn. Res., 2022
Greedy-layer pruning: Speeding up transformer models for natural language processing.
Pattern Recognit. Lett., 2022
Proceedings of the 5th IEEE International Conference on Image Processing Applications and Systems, 2022
Proceedings of the 5th IEEE International Conference on Image Processing Applications and Systems, 2022
Deep Learning for Fast Segmentation of E-waste Devices' Inner Parts in a Recycling Scenario.
Proceedings of the Pattern Recognition and Artificial Intelligence, 2022
Proceedings of the 21st IEEE-RAS International Conference on Humanoid Robots, 2022
2021
conflicting_bundle.py - A python module to identify problematic layers in deep neural networks.
Softw. Impacts, 2021
Arguments for the unsuitability of convolutional neural networks for non-local tasks.
Neural Networks, 2021
Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021
2020
A robust contour detection operator with combined push-pull inhibition and surround suppression.
Inf. Sci., 2020
Improving CT Image Tumor Segmentation Through Deep Supervision and Attentional Gates.
Frontiers Robotics AI, 2020
Proceedings of the 29th IEEE International Symposium on Industrial Electronics, 2020
Proceedings of the 29th IEEE International Symposium on Industrial Electronics, 2020
2019
Towards affordance detection for robot manipulation using affordance for parts and parts for affordance.
Auton. Robots, 2019
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019
2018
IEEE Robotics Autom. Lett., 2018
ISLES Challenge: U-Shaped Convolution Neural Network with Dilated Convolution for 3D Stroke Lesion Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
2017
Proceedings of the 2017 IEEE Winter Conference on Applications of Computer Vision, 2017
A deep learning approach for detecting and correcting highlights in endoscopic images.
Proceedings of the Seventh International Conference on Image Processing Theory, 2017
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017
2016
Mach. Vis. Appl., 2016
Monocular obstacle avoidance for blind people using probabilistic focus of expansion estimation.
Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016
Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2016
2015
Beyond Simple and Complex Neurons: Towards Intermediate-level Representations of Shapes and Objects.
Künstliche Intell., 2015
Frontiers Comput. Neurosci., 2015
Editorial: Hierarchical Object Representations in the Visual Cortex and Computer Vision.
Frontiers Comput. Neurosci., 2015
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015
Proceedings of the 12th Conference on Computer and Robot Vision, 2015
Proceedings of the Working Notes of CLEF 2015, 2015
Proceedings of the Computer Analysis of Images and Patterns, 2015
2014
Towards Sparsity and Selectivity: Bayesian Learning of Restricted Boltzmann Machine for Early Visual Features.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014
2013
Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?
IEEE Trans. Pattern Anal. Mach. Intell., 2013
ÖAGM/AAPR 2013 - The 37th Annual Workshop of the Austrian Association for Pattern Recognition
CoRR, 2013
Proceedings of the 37th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), 2013
CoRR, 2013
Models of the Visual Cortex for Object Representation: Learning and Wired Approaches.
Proceedings of the Brain-Inspired Computing - International Workshop, 2013
Proceedings of the Shape Perception in Human and Computer Vision, 2013
2011
The importance of intermediate representations for the modeling of 2D shape detection: Endstopping and curvature tuned computations.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011
2008
Int. J. Pattern Recognit. Artif. Intell., 2008
2007
Proceedings of the Advances in Brain, 2007
2006
Proceedings of the Artificial Neural Networks, 2006